Pandas Profiling Report

Dataset statistics

Number of variables	39
Number of observations	10324
Missing cells	3706
Missing cells (%)	0.9%
Duplicate rows	31
Duplicate rows (%)	0.3%
Total size in memory	3.1 MiB
Average record size in memory	312.0 B

Variable types

Numeric	8
Categorical	31

Alerts

Dataset has 31 (0.3%) duplicate rows	Duplicates
`Line Item Quantity` is highly correlated with `Line Item Value` and 3 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price` and 1 other fields	High correlation
`Unit Price` is highly correlated with `Pack Price` and 3 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Unit Price` and 4 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit Price` and 4 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Pack Price` and 5 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 1 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Insurance (USD)`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 2 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price`	High correlation
`Unit Price` is highly correlated with `Pack Price`	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Weight (Kilograms)`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 5 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Adult` is highly correlated with `Product Group_ARV` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Vendor INCO Term_EXW` and 3 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Sub Classification_Adult` and 3 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`Sub Classification_Adult` is highly correlated with `Sub Classification_HIV test` and 3 other fields	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Sub Classification_ACT` is highly correlated with `Product Group_ACT`	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM`	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_From RDC` and 2 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_HRDT` is highly correlated with `Sub Classification_HIV test` and 3 other fields	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Product Group_ARV` is highly correlated with `Sub Classification_HIV test` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_From RDC` and 5 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`Product Group_ACT` is highly correlated with `Sub Classification_ACT`	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Product Group_ACT` and 4 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 1 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_Ethiopia Field Office` is highly correlated with `Managed By_Haiti Field Office`	High correlation
`Managed By_Haiti Field Office` is highly correlated with `Managed By_Ethiopia Field Office`	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 6 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 8 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Vendor INCO Term_DDP` and 2 other fields	High correlation
`Shipment Mode_Truck` is highly correlated with `Vendor INCO Term_EXW` and 1 other fields	High correlation
`Product Group_ACT` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Product Group_ARV` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_ACT` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Sub Classification_Adult` is highly correlated with `Vendor INCO Term_EXW` and 4 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Fulfill Via_Direct Drop` and 6 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Unit of Measure (Per Pack)` and 2 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Weight (Kilograms)` has 1633 (15.8%) missing values	Missing
`Freight Cost (USD)` has 1786 (17.3%) missing values	Missing
`Line Item Insurance (USD)` has 287 (2.8%) missing values	Missing
`Unit Price` is highly skewed (γ1 = 40.58484939)	Skewed
`Weight (Kilograms)` is highly skewed (γ1 = 33.03598689)	Skewed

Reproduction

Analysis started	2022-05-21 12:07:59.098396
Analysis finished	2022-05-21 12:08:22.676172
Duration	23.58 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Unit of Measure (Per Pack)
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	31
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	77.990895

Minimum	1
Maximum	1000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	1
5-th percentile	20
Q1	30
median	60
Q3	90
95-th percentile	240
Maximum	1000
Range	999
Interquartile range (IQR)	60

Descriptive statistics

Standard deviation	76.57976396
Coefficient of variation (CV)	0.9819064643
Kurtosis	36.09399876
Mean	77.990895
Median Absolute Deviation (MAD)	30
Skewness	4.302502487
Sum	805178
Variance	5864.460248
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
60	4121	39.9%
30	2630	25.5%
100	976	9.5%
240	670	6.5%
120	474	4.6%
20	470	4.6%
90	222	2.2%
300	157	1.5%
1	126	1.2%
25	114	1.1%
Other values (21)	364	3.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	126	1.2%
2	4	< 0.1%
3	8	0.1%
5	4	< 0.1%
12	2	< 0.1%
18	4	< 0.1%
20	470	4.6%
24	2	< 0.1%
25	114	1.1%
30	2630	25.5%

Value	Count	Frequency (%)
1000	16	0.2%
720	5	< 0.1%
540	7	0.1%
336	39	0.4%
300	157	1.5%
270	53	0.5%
240	670	6.5%
200	76	0.7%
180	76	0.7%
168	3	< 0.1%

Line Item Quantity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5065
Distinct (%)	49.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18332.53487

Minimum	1
Maximum	619999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	1
5-th percentile	17
Q1	408
median	3000
Q3	17039.75
95-th percentile	90951.55
Maximum	619999
Range	619998
Interquartile range (IQR)	16631.75

Descriptive statistics

Standard deviation	40035.30296
Coefficient of variation (CV)	2.18383891
Kurtosis	40.0503001
Mean	18332.53487
Median Absolute Deviation (MAD)	2950
Skewness	5.038314699
Sum	189265090
Variance	1602825483
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	93	0.9%
1000	91	0.9%
100	87	0.8%
2000	73	0.7%
5000	69	0.7%
500	67	0.6%
20000	67	0.6%
3000	66	0.6%
3	63	0.6%
50000	62	0.6%
Other values (5055)	9586	92.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	35	0.3%
2	40	0.4%
3	63	0.6%
4	46	0.4%
5	28	0.3%
6	48	0.5%
7	27	0.3%
8	26	0.3%
9	22	0.2%
10	54	0.5%

Value	Count	Frequency (%)
619999	1	< 0.1%
600906	1	< 0.1%
555197	1	< 0.1%
515000	3	< 0.1%
514526	1	< 0.1%
460041	1	< 0.1%
440000	1	< 0.1%
438409	1	< 0.1%
401961	1	< 0.1%
400000	2	< 0.1%

Line Item Value
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	8741
Distinct (%)	84.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	157650.5673

Minimum	0
Maximum	5951990.4
Zeros	17
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	0
5-th percentile	192.5755
Q1	4314.5925
median	30471.465
Q3	166447.14
95-th percentile	702831
Maximum	5951990.4
Range	5951990.4
Interquartile range (IQR)	162132.5475

Descriptive statistics

Standard deviation	345292.067
Coefficient of variation (CV)	2.190236755
Kurtosis	54.15243042
Mean	157650.5673
Median Absolute Deviation (MAD)	29920.465
Skewness	5.837020186
Sum	1627584457
Variance	1.192266115 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
200000	29	0.3%
16000	23	0.2%
800	18	0.2%
0	17	0.2%
14400	16	0.2%
244216	15	0.1%
3200	15	0.1%
120000	13	0.1%
250	11	0.1%
160	11	0.1%
Other values (8731)	10156	98.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	17	0.2%
0.01	1	< 0.1%
0.03	1	< 0.1%
0.12	1	< 0.1%
0.2	1	< 0.1%
0.24	1	< 0.1%
0.25	1	< 0.1%
0.42	1	< 0.1%
0.5	1	< 0.1%
0.7	1	< 0.1%

Value	Count	Frequency (%)
5951990.4	1	< 0.1%
5768697.6	1	< 0.1%
5329891.2	1	< 0.1%
5140114.74	1	< 0.1%
4959241.98	1	< 0.1%
4278871.84	1	< 0.1%
4228629.72	1	< 0.1%
4014000	1	< 0.1%
3932880	1	< 0.1%
3904000	2	< 0.1%

Pack Price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	1175
Distinct (%)	11.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	21.91024119

Minimum	0
Maximum	1345.64
Zeros	18
Zeros (%)	0.2%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	0
5-th percentile	1.9
Q1	4.12
median	9.3
Q3	23.5925
95-th percentile	80
Maximum	1345.64
Range	1345.64
Interquartile range (IQR)	19.4725

Descriptive statistics

Standard deviation	45.60922308
Coefficient of variation (CV)	2.081639481
Kurtosis	293.1762044
Mean	21.91024119
Median Absolute Deviation (MAD)	6.57
Skewness	12.98843214
Sum	226201.33
Variance	2080.20123
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32	368	3.6%
80	307	3.0%
89	183	1.8%
11.22	139	1.3%
20	110	1.1%
8.76	91	0.9%
1.95	91	0.9%
2.44	90	0.9%
2.1	89	0.9%
2.26	88	0.9%
Other values (1165)	8768	84.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	18	0.2%
0.01	85	0.8%
0.39	2	< 0.1%
0.7	2	< 0.1%
0.9	4	< 0.1%
1.1	2	< 0.1%
1.14	2	< 0.1%
1.17	1	< 0.1%
1.2	1	< 0.1%
1.21	1	< 0.1%

Value	Count	Frequency (%)
1345.64	1	< 0.1%
1250	1	< 0.1%
1242.53	3	< 0.1%
750.29	1	< 0.1%
700	1	< 0.1%
400	9	0.1%
350	39	0.4%
308.17	3	< 0.1%
306.88	3	< 0.1%
301.53	1	< 0.1%

Unit Price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
SKEWED

Distinct	183
Distinct (%)	1.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.6117008911

Minimum	0
Maximum	238.65
Zeros	103
Zeros (%)	1.0%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.01
Q1	0.08
median	0.16
Q3	0.47
95-th percentile	1.6
Maximum	238.65
Range	238.65
Interquartile range (IQR)	0.39

Descriptive statistics

Standard deviation	3.275807741
Coefficient of variation (CV)	5.35524435
Kurtosis	2725.960252
Mean	0.6117008911
Median Absolute Deviation (MAD)	0.12
Skewness	40.58484939
Sum	6315.2
Variance	10.73091635
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.04	713	6.9%
0.01	492	4.8%
0.12	464	4.5%
0.14	444	4.3%
0.8	411	4.0%
0.11	400	3.9%
1.6	368	3.6%
0.05	343	3.3%
0.16	343	3.3%
0.19	321	3.1%
Other values (173)	6025	58.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	103	1.0%
0.01	492	4.8%
0.02	140	1.4%
0.03	250	2.4%
0.04	713	6.9%
0.05	343	3.3%
0.06	274	2.7%
0.07	248	2.4%
0.08	146	1.4%
0.09	154	1.5%

Value	Count	Frequency (%)
238.65	1	< 0.1%
41.68	1	< 0.1%
37.5	2	< 0.1%
30	1	< 0.1%
26.91	1	< 0.1%
25	4	< 0.1%
24.85	3	< 0.1%
24.5	46	0.4%
23	23	0.2%
17.12	3	< 0.1%

Weight (Kilograms)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
SKEWED

Distinct	3388
Distinct (%)	39.0%
Missing	1633
Missing (%)	15.8%
Infinite	0
Infinite (%)	0.0%
Mean	4464.293407

Minimum	0
Maximum	857354
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	0
5-th percentile	25
Q1	275
median	1303
Q3	4364
95-th percentile	18141
Maximum	857354
Range	857354
Interquartile range (IQR)	4089

Descriptive statistics

Standard deviation	13372.40941
Coefficient of variation (CV)	2.995414545
Kurtosis	1942.060991
Mean	4464.293407
Median Absolute Deviation (MAD)	1213
Skewness	33.03598689
Sum	38799174
Variance	178821333.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
112	31	0.3%
54	30	0.3%
2	29	0.3%
6	28	0.3%
1	23	0.2%
46	23	0.2%
12	21	0.2%
13	20	0.2%
5	20	0.2%
60	20	0.2%
Other values (3378)	8446	81.8%
(Missing)	1633	15.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	23	0.2%
2	29	0.3%
3	19	0.2%
4	19	0.2%
5	20	0.2%
6	28	0.3%
7	16	0.2%
8	14	0.1%
9	17	0.2%

Value	Count	Frequency (%)
857354	1	< 0.1%
291096	1	< 0.1%
205503	1	< 0.1%
154780	1	< 0.1%
112027	3	< 0.1%
90446	2	< 0.1%
88761	5	< 0.1%
88190	1	< 0.1%
87076	2	< 0.1%
85128	1	< 0.1%

Freight Cost (USD)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5432
Distinct (%)	63.6%
Missing	1786
Missing (%)	17.3%
Infinite	0
Infinite (%)	0.0%
Mean	12641.90846

Minimum	0.75
Maximum	289653.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	0.75
5-th percentile	732.2225
Q1	2599.09
median	6759.28
Q3	15571.48
95-th percentile	43548
Maximum	289653.2
Range	289652.45
Interquartile range (IQR)	12972.39

Descriptive statistics

Standard deviation	18189.92402
Coefficient of variation (CV)	1.43885902
Kurtosis	27.76382653
Mean	12641.90846
Median Absolute Deviation (MAD)	5067.96
Skewness	4.189276228
Sum	107936614.4
Variance	330873335.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9736.1	37	0.4%
7445.8	28	0.3%
6147.18	27	0.3%
7329.83	20	0.2%
9341.49	19	0.2%
13398.06	18	0.2%
9869.55	17	0.2%
17090	16	0.2%
20499.33	15	0.1%
3918.37	15	0.1%
Other values (5422)	8326	80.6%
(Missing)	1786	17.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.75	1	< 0.1%
14.36	2	< 0.1%
17.72	1	< 0.1%
22.29	1	< 0.1%
29.21	3	< 0.1%
30	1	< 0.1%
30.49	1	< 0.1%
41	1	< 0.1%
42.35	1	< 0.1%
48	1	< 0.1%

Value	Count	Frequency (%)
289653.2	1	< 0.1%
241407.27	1	< 0.1%
194623.44	2	< 0.1%
161962.32	1	< 0.1%
161712.87	13	0.1%
152368.7	1	< 0.1%
146850.66	1	< 0.1%
146734.85	1	< 0.1%
139951.34	1	< 0.1%
132890.27	4	< 0.1%

Line Item Insurance (USD)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	6722
Distinct (%)	67.0%
Missing	287
Missing (%)	2.8%
Infinite	0
Infinite (%)	0.0%
Mean	240.1176258

Minimum	0
Maximum	7708.44
Zeros	54
Zeros (%)	0.5%
Negative	0
Negative (%)	0.0%
Memory size	80.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.25
Q1	6.51
median	47.04
Q3	252.4
95-th percentile	1082.032
Maximum	7708.44
Range	7708.44
Interquartile range (IQR)	245.89

Descriptive statistics

Standard deviation	500.1905677
Coefficient of variation (CV)	2.083106419
Kurtosis	34.91121486
Mean	240.1176258
Median Absolute Deviation (MAD)	46.27
Skewness	4.827162374
Sum	2410060.61
Variance	250190.604
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	54	0.5%
0.02	37	0.4%
0.07	33	0.3%
0.05	30	0.3%
0.06	30	0.3%
0.01	26	0.3%
0.03	23	0.2%
0.09	21	0.2%
0.08	20	0.2%
0.12	18	0.2%
Other values (6712)	9745	94.4%
(Missing)	287	2.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	54	0.5%
0.01	26	0.3%
0.02	37	0.4%
0.03	23	0.2%
0.04	14	0.1%
0.05	30	0.3%
0.06	30	0.3%
0.07	33	0.3%
0.08	20	0.2%
0.09	21	0.2%

Value	Count	Frequency (%)
7708.44	1	< 0.1%
7005.49	1	< 0.1%
5930.22	1	< 0.1%
5573.31	1	< 0.1%
5479.13	1	< 0.1%
5284.04	1	< 0.1%
5230.81	1	< 0.1%
5162.29	1	< 0.1%
5145	2	< 0.1%
5098.1	1	< 0.1%

Managed By_Ethiopia Field Office
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10323
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10323	> 99.9%
1	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10323	> 99.9%
1	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_Haiti Field Office
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10323
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10323	> 99.9%
1	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10323	> 99.9%
1	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_PMO - US
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	10265
0	59

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	10265	99.4%
0	59	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	10265	99.4%
0	59	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_South Africa Field Office
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10267
1	57

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10267	99.4%
1	57	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10267	99.4%
1	57	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_Direct Drop
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	5404
1	4920

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	5404	52.3%
1	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	5404	52.3%
1	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	5404
0	4920

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	5404	52.3%
0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	5404	52.3%
0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIF
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10321
1	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10321	> 99.9%
1	3	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10321	> 99.9%
1	3	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIP
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10049
1	275

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10049	97.3%
1	275	2.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10049	97.3%
1	275	2.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DAP
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10315
1	9

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10315	99.9%
1	9	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10315	99.9%
1	9	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDP
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	8881
1	1443

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8881	86.0%
1	1443	14.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8881	86.0%
1	1443	14.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDU
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10309
1	15

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10309	99.9%
1	15	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10309	99.9%
1	15	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_EXW
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	7546
1	2778

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
0	7546	73.1%
1	2778	26.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	7546	73.1%
1	2778	26.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_FCA
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	9927
1	397

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9927	96.2%
1	397	3.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9927	96.2%
1	397	3.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_N/A - From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	5404
0	4920

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	5404	52.3%
0	4920	47.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	5404	52.3%
0	4920	47.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	6113
0	4211

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	6113	59.2%
0	4211	40.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	6113	59.2%
0	4211	40.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air Charter
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	9674
1	650

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9674	93.7%
1	650	6.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9674	93.7%
1	650	6.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Ocean
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	9953
1	371

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9953	96.4%
1	371	3.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9953	96.4%
1	371	3.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Truck
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	7494
1	2830

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	7494	72.6%
1	2830	27.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	7494	72.6%
1	2830	27.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ACT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10308
1	16

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10308	99.8%
1	16	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10308	99.8%
1	16	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ANTM
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10302
1	22

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10302	99.8%
1	22	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10302	99.8%
1	22	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ARV
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	8550
0	1774

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	8550	82.8%
0	1774	17.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	8550	82.8%
0	1774	17.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_HRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	8596
1	1728

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8596	83.3%
1	1728	16.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8596	83.3%
1	1728	16.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_MRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10316
1	8

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10316	99.9%
1	8	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10316	99.9%
1	8	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_ACT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10308
1	16

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10308	99.8%
1	16	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10308	99.8%
1	16	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Adult
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	6595
0	3729

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	6595	63.9%
0	3729	36.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	6595	63.9%
0	3729	36.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	8757
1	1567

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8757	84.8%
1	1567	15.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8757	84.8%
1	1567	15.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test - Ancillary
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10163
1	161

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10163	98.4%
1	161	1.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10163	98.4%
1	161	1.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Malaria
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	10294
1	30

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	10294	99.7%
1	30	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	10294	99.7%
1	30	0.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Pediatric
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	8369
1	1955

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8369	81.1%
1	1955	18.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8369	81.1%
1	1955	18.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_No
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

0	7030
1	3294

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	7030	68.1%
1	3294	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	7030	68.1%
1	3294	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_Yes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	80.8 KiB

1	7030
0	3294

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	7030	68.1%
0	3294	31.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	7030	68.1%
0	3294	31.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_Direct Drop	Vendor INCO Term_CIP	Vendor INCO Term_DDU	Vendor INCO Term_EXW	Vendor INCO Term_FCA	Shipment Mode_Air	Product Group_ARV	Product Group_HRDT	Sub Classification_Adult	Sub Classification_HIV test	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
0	30	19	551.00	29.00	0.97	13.0	780.34	NaN	1	1	0	0	1	0	1	0	1	0	1	0	0	1
1	240	1000	6200.00	6.20	0.03	358.0	4521.50	NaN	1	1	0	0	1	0	1	1	0	0	0	1	0	1
2	100	500	40000.00	80.00	0.80	171.0	1653.78	NaN	1	1	0	0	0	1	1	0	1	0	1	0	0	1
3	60	31920	127360.80	3.99	0.07	1855.0	16007.06	NaN	1	1	0	0	1	0	1	1	0	1	0	0	0	1
4	60	38000	121600.00	3.20	0.05	7590.0	45450.08	NaN	1	1	0	0	1	0	1	1	0	1	0	0	0	1
5	240	416	2225.60	5.35	0.02	504.0	5920.42	NaN	1	1	0	0	1	0	1	1	0	0	0	1	0	1
6	90	135	4374.00	32.40	0.36	328.0	NaN	NaN	1	1	0	1	0	0	1	1	0	0	0	1	0	1
7	60	16667	60834.55	3.65	0.06	1478.0	6212.41	NaN	1	1	0	0	1	0	1	1	0	1	0	0	0	1
8	60	273	532.35	1.95	0.03	479.0	4861.14	NaN	1	1	0	0	1	0	1	1	0	1	0	0	1	0
9	120	2800	115080.00	41.10	0.34	643.0	NaN	NaN	1	1	1	0	0	0	1	1	0	1	0	0	0	1

Last rows

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_From RDC	Vendor INCO Term_N/A - From RDC	Shipment Mode_Air	Shipment Mode_Air Charter	Shipment Mode_Truck	Product Group_ARV	Sub Classification_Adult	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
10314	60	10340	37224.00	3.60	0.06	6295.0	16941.00	38.27	1	1	1	0	1	0	1	0	1	1	0
10315	120	70000	1304800.00	18.64	0.16	15198.0	26180.00	1341.33	1	1	1	0	1	0	1	1	0	0	1
10316	60	15000	97800.00	6.52	0.11	1547.0	3410.00	115.11	1	1	1	0	1	0	1	1	0	0	1
10317	30	6724	20978.88	3.12	0.10	6183.0	47281.56	24.69	1	1	1	1	0	0	1	1	0	1	0
10318	60	205243	738874.80	3.60	0.06	25880.0	46111.55	869.66	1	1	1	0	0	1	1	0	1	1	0
10319	60	166571	599655.60	3.60	0.06	25880.0	46111.55	705.79	1	1	1	0	0	1	1	0	1	1	0
10320	60	21072	137389.44	6.52	0.11	4426.0	14734.92	161.71	1	1	1	0	0	1	1	1	0	1	0
10321	30	514526	5140114.74	9.99	0.33	NaN	NaN	5284.04	1	1	1	0	0	1	1	1	0	1	0
10322	60	17465	113871.80	6.52	0.11	1392.0	NaN	134.03	1	1	1	0	0	1	1	1	0	0	1
10323	60	36639	72911.61	1.99	0.03	NaN	NaN	85.82	1	1	1	0	0	1	1	0	1	1	0

Most frequently occurring

	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_Direct Drop	Vendor INCO Term_EXW	Shipment Mode_Air	Product Group_HRDT	Sub Classification_HIV test	Sub Classification_HIV test - Ancillary	First Line Designation_No	First Line Designation_Yes	# duplicates
23	100	2744	244216.0	89.0	0.89	1186.0	24927.19	342.39	1	1	1	1	1	1	0	0	1	6
0	1	2988	73206.0	24.5	24.50	1992.0	26266.34	90.56	1	1	1	1	1	1	0	0	1	5
1	1	3510	80730.0	23.0	23.00	2535.0	20083.74	158.23	1	1	1	1	1	1	0	0	1	3
25	100	2744	244216.0	89.0	0.89	1303.0	28734.43	342.39	1	1	1	1	1	1	0	0	1	3
2	1	3510	80730.0	23.0	23.00	2535.0	23035.69	158.23	1	1	1	1	1	1	0	0	1	2
3	1	5994	146853.0	24.5	24.50	3996.0	53062.21	150.96	1	1	1	1	1	1	0	0	1	2
4	1	6998	160954.0	23.0	23.00	5057.0	44347.71	257.53	1	1	1	1	1	1	0	0	1	2
5	1	7002	161046.0	23.0	23.00	5057.0	44347.71	257.67	1	1	1	1	1	1	0	0	1	2
6	3	10	250.0	25.0	8.33	6.0	418.94	0.49	1	1	1	1	1	0	1	0	1	2
7	20	25	800.0	32.0	1.60	176.0	4124.74	0.99	1	1	1	1	1	1	0	1	0	2

Overview

Variables

Common Values

Length

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Most occurring characters

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Most occurring scripts

Most frequent character per script

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Most frequent character per block

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Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

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Most frequent character per block

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Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

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Most frequent character per block

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Length

Pie chart

Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

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Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script